Immunotherapy In Non-small Cell Lung Cancer Research Articles

Triple-induction treatment for locally advanced non-small cell lung cancer: a case report of pathological complete response

BackgroundIn patients with resectable stage III non-small cell lung cancer (NSCLC), induction chemoimmunotherapy followed by surgical resection has shown unprecedented rates of pathological response and event-free survival. However, a triple-induction including radiochemotherapy and immunotherapy followed by surgical resection has not been routinely established in clinical practice.Case presentationWe report the case of a 47-year-old patient with stage IIIA NSCLC who was treated in a combined concept including induction concurrent radiochemotherapy, followed by 4 cycles of pembrolizumab and subsequent intrapericardial left-sided pneumonectomy. Histological analysis revealed a pathological complete response.ConclusionsThe case demonstrates that the combination of neoadjuvant chemo-, radio- and immunotherapy in advanced NSCLC may lead to a relevant down-staging and may enable a R0-resection of a borderline resectable tumor. However, the combination of four different treatment modalities requires resilience and a good performance status. A triple induction treatment may be a promising option for selected patients with locally advanced NSCLC and good performance status.

Photodynamic therapy upregulates expression of HIF-1α and PD-L1 in related pathways and its clinical relevance in non-small-cell lung cancer

BackgroundPhotodynamic therapy (PDT) is a promising interventional treatment approach that contributes to antitumor immunity. It has been reported that PDT can enhance the effectiveness of immune checkpoint inhibitors (ICIs), but its mechanism is yet unclear. Herein, we implemented bioinformatics analysis to detect common pathways and potential biomarkers in non-small cell lung cancer (NSCLC), PDT, and NSCLC immunotherapy to investigate potential links between PDT, immunotherapy and NSCLC, and their clinical impact.MethodsDifferentially expressed genes in NSCLC- and NSCLC immunotherapy-related data in the GEO database were intersected with PDT-related genes in the GeneCards database to obtain candidate genes and shared pathways. Enrichment analysis and protein–protein interaction were established to identify key genes in functionally enriched pathways. The expression profiles and the prognostic significance of key genes were depicted.ResultsBioinformatics analysis showed that HIF-1α was screened as a prognostic gene in hypoxia, HIF-1, and PD-L1-related signaling pathways, which was associated with clinical response in NSCLC patients after PDT and immunotherapy. In vivo experiments showed that PDT could inhibit tumor growth and upregulate HIF-1α and PD-L1 expressions in NSCLC tissues with a positive correlation, which might influence the blocking activity of ICIs on the HIF-1, and PD-L1-related signaling pathways.ConclusionsPDT might improve the clinical response of ICIs by upregulating tumor HIF-1α and PD-L1 expressions in NSCLC.

Mechanisms of resistance to targeted therapy and immunotherapy in non-small cell lung cancer: promising strategies to overcoming challenges

Resistance to targeted therapy and immunotherapy in non-small cell lung cancer (NSCLC) is a significant challenge in the treatment of this disease. The mechanisms of resistance are multifactorial and include molecular target alterations and activation of alternative pathways, tumor heterogeneity and tumor microenvironment change, immune evasion, and immunosuppression. Promising strategies for overcoming resistance include the development of combination therapies, understanding the resistance mechanisms to better use novel drug targets, the identification of biomarkers, the modulation of the tumor microenvironment and so on. Ongoing research into the mechanisms of resistance and the development of new therapeutic approaches hold great promise for improving outcomes for patients with NSCLC. Here, we summarize diverse mechanisms driving resistance to targeted therapy and immunotherapy in NSCLC and the latest potential and promising strategies to overcome the resistance to help patients who suffer from NSCLC.

CONTACT-01: A Randomized Phase III Trial of Atezolizumab + Cabozantinib Versus Docetaxel for Metastatic Non-Small Cell Lung Cancer After a Checkpoint Inhibitor and Chemotherapy.

Although checkpoint inhibitors have improved first-line treatment for non-small cell lung cancer (NSCLC), a therapeutic need remains for patients whose disease does not respond or who experience disease progression after anti-PD-L1/PD-1 immunotherapy. CONTACT-01 (ClinicalTrials.gov identifier: NCT04471428) evaluated atezolizumab plus cabozantinib versus docetaxel in patients with metastatic NSCLC who developed disease progression after concurrent or sequential treatment with anti-PD-L1/PD-1 and platinum-containing chemotherapy. This multicenter, open-label, phase III trial randomly assigned patients 1:1 to atezolizumab 1,200 mg intravenously once every 3 weeks (q3w) plus cabozantinib 40 mg orally once daily or docetaxel 75 mg/m2 intravenously once every 3 weeks. The primary end point was overall survival (OS). One hundred eighty-six patients were assigned atezolizumab plus cabozantinib, and 180 docetaxel. Minimum OS follow-up was 10.9 months. Median OS was 10.7 months (95% CI, 8.8 to 12.3) with atezolizumab plus cabozantinib and 10.5 months (95% CI, 8.6 to 13.0) with docetaxel (stratified hazard ratio [HR], 0.88 [95% CI, 0.68 to 1.16]; P = .3668). Median progression-free survival was 4.6 months (95% CI, 4.1 to 5.6) and 4.0 months (95% CI, 3.1 to 4.4), respectively (stratified HR, 0.74 [95% CI, 0.59 to 0.92]). Serious adverse events (AEs) occurred in 71 (38.4%) patients receiving atezolizumab plus cabozantinib and 58 (34.7%) receiving docetaxel. Grade 3/4 treatment-related AEs occurred in 73 (39.5%) patients receiving atezolizumab plus cabozantinib and 58 (34.7%) receiving docetaxel. Grade 5 AEs occurred in 14 (7.6%) and 10 (6.0%) patients in the atezolizumab plus cabozantinib and docetaxel arms, respectively (treatment-related in four [2.2%] and one [0.6%], respectively). Atezolizumab plus cabozantinib after disease progression following anti-PD-L1/PD-1 immunotherapy and platinum-containing chemotherapy for metastatic NSCLC did not improve OS compared with docetaxel. Safety was consistent with known profiles of these agents.

Prediction performance comparison of biomarkers for response to immune checkpoint inhibitors in advanced non-small cell lung cancer.

The aim of the present study was to compare the predictive accuracy of PD-L1 immunohistochemistry (IHC), tissue or blood tumor mutation burden (tTMB, bTMB), gene expression profile (GEP), driver gene mutation, and combined biomarkers for immunotherapy response of advanced non-small cell lung cancer (NSCLC). In part 1, clinical trials involved with predictive biomarker exploration for immunotherapy in advanced NSCLC were included. The area under the curve (AUC) of the summary receiver operating characteristic (SROC), sensitivity, specificity, likelihood ratio and predictive value of the biomarkers were evaluated. In part 2, public datasets of immune checkpoint inhibitor (ICI)-treated NSCLC involved with biomarkers were curated (N = 871). Odds ratio (OR) of the positive versus negative biomarker group for objective response rate (ORR) was measured. In part 1, the AUC of combined biomarkers (0.75) was higher than PD-L1 (0.64), tTMB (0.64), bTMB (0.68), GEP (0.67), and driver gene mutation (0.51). Combined biomarkers also had higher specificity, positive likelihood ratio and positive predictive value than single biomarkers. In part 2, the OR of combined biomarkers of PD-L1 plus TMB (PD-L1 cutoff 1%, 0.14; cutoff 50% 0.13) was lower than that of PD-L1 (cutoff 1%, 0.33; cutoff 50% 0.24), tTMB (0.28), bTMB (0.48), EGFR mutation (0.17) and KRAS mutation (0.47), for distinguishing ORR of patients after immunotherapy. Furthermore, positive PD-L1, tTMB-high, wild-type EGFR, and positive PD-L1 plus TMB were associated with prolonged progression-free survival (PFS). Combined biomarkers have superior predictive accuracy than single biomarkers for immunotherapy response of NSCLC. Further investigation is warranted to select optimal biomarkers for various clinical settings.

Abstract 2531: rs822336 as a predictive biomarker for anti-PD-1/PD-L1 immunotherapy in advanced NSCLC: Unraveling molecular mechanisms

Abstract Efficient predictive biomarkers are needed for immune checkpoint inhibitor (ICI)-based immunotherapy in non-small-cell lung cancer (NSCLC). So far, testing the predictive value of single nucleotide polymorphisms (SNPs) in programmed cell death 1 (PD-1) or its ligand 1 (PD-L1) has shown contrasting results. Here, we aimed to validate the predictive value of PD-L1 SNPs in advanced NSCLC patients treated with ICIs as well as to define the molecular mechanisms underlying the role of identified SNP candidate. rs822336 SNP efficiently predicted response to anti-PD-1/PD-L1-based immunotherapy in advanced NSCLC patients as compared to rs2282055 and rs4143815 SNPs. rs822336 SNP mapped on promoter/enhancer region of PD-L1, differentially affecting the induction of PD-L1 expression in human NSCLC cell lines. The induction of PD-L1 expression by rs822336 SNP was predicted by allele-specificity binding of two identified transcription factors: C/EBPβ and NFIC. As a result, silencing of C/EBPβ and NFIC differentially modulated the induction of PD-L1 expression in human NSCLC cell lines carrying different rs822336 genotypes. In addition, binding microarray validated the allele- specificity binding of C/EBPβ and NFIC to PD-L1 promoter/enhancer region based on rs822336 genotype in human NSCLC cell lines. Lastly, the induction of PD-L1 expression by rs822336 genotype differentially affected the susceptibility to anti-PD-1 monoclonal antibody nivolumab of human NSCLC cell lines co-cultured with HLA class I antigen matched PBMC. These results have clinical relevance since identified rs822336 SNP and the induction of PD-L1 expression as novel biomarkers for predicting ICI-based immunotherapy in NSCLC patients. Citation Format: Giovanna Polcaro, Luigi Liguori, Valentina Manzo, Annalisa Chianese, Giuliana Donadio, Alessandro Caputo, Giosuè Scognamiglio, Federica Dell'Annunziata, Maddalena Langella, Graziamaria Corbi, Alessandro Ottaiano, Marco Cascella, Francesco Perri, Margot De Marco, Jessica Dal Col, Valentina Pagliara, Pio Zeppa, Amelia Filippelli, Gianluigi Franci, Fabrizio Dal Piaz, Valeria Conti, Stefano Pepe, Francesco Sabbatino. rs822336 as a predictive biomarker for anti-PD-1/PD-L1 immunotherapy in advanced NSCLC: Unraveling molecular mechanisms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2531.

Abstract 6391: Spatial proteomic profiling unveils pre-existing anti-tumor immunity as a hallmark of exceptional benefit from immunotherapy in NSCLC

Abstract Background: Immunotherapy is firmly established as a treatment regimen in various solid tumors due to its exceptional benefits observed in a select group of patients. Despite widespread use of immune checkpoint blockade (ICB) across diverse solid tumors, including non-small cell lung cancer (NSCLC), the quest for a clinically informative biomarker for long-term benefit remains unmet. Here we investigate the potential utility of clinicopathological and spatial proteomic profiling of tumor specimens from NSCLC patients to identify predictive biomarkers of long-term benefit to ICB. Methods: Forty-nine patients diagnosed with advanced NSCLC who received ICB at Hospital del Mar, Barcelona between 2017-2021 were included. Long-term responders (LTR, n=21) were defined as patients achieving a maintained radiologic response for more than 2 years, and short-term responders (STR, n=28) as patients presenting disease progression within the first six months of ICB initiation. Clinicopathological information, incidence of immune related adverse (irAES) and PD-L1 tumor proportion score assessed by IHC was available for all of them. DSP GeoMx was performed in subset of patients (LTR n=14 and STR n=14), to assess 49 immune biomarkers. Pancytokeratin (panCK; epithelial), CD3, CD20 and SYTO 13 (nuclear) were utilized as morphology biomarkers. Regions of interest were placed in tissue areas containing tumor and segmented in Tumor (PanCK+) and tumor microenvironment (TME) (PanCK-) that was used on downstream analysis. Digital counts were normalized using the protein expression of housekeeper proteins. Statistical analysis was performed using linear mixed models. A P value less than 0.05 was considered significant. Results: Our analysis revealed specific characteristics of LTR patients compared with STR, namely LTR population was enriched for PD-L1 positive in tumors (p=0.005) and a higher incidence of immune-related adverse events (irAEs) (p=0.001). Within the Tumor compartment, LTR patients displayed significantly higher levels of IDO1, CD8, PD-L1, CD45, HLA-DR and STING, while STR patients exhibit higher levels of B7-H3, CD56 and OX40L (p<0.05 for all proteins). Comparison analysis of the TME compartment between LTR and STR revealed augmented levels of IDO1, CD8, CD45, CD11c, CD27 and CD3 in LTR patients, and lower levels of B7H3 and OX40L compared with STR patients (p<0.05 for all proteins). Conclusions: Our comprehensive analysis of metastatic NSCLC patients treated with ICB has unveiled distinct clinicopathological and immunological features associated with long-term benefit of ICB, highlighting the presence of pre-existing antitumor immunity as a stronger predictor of long-term benefit. These findings offer insights into potential biomarkers and therapeutic strategies for enhancing ICB outcomes in metastatic NSCLC. Citation Format: Sharia Hernandez, Rafael Bach, Mario Giner, Wei Lu, Larisa Kostousov, Sean Barnes, Khaja Khan, Laura Masfarré, Xavier Villanueva, Ignacio Sanchéz, Nil Navarro, Álvaro Taus, Miguel Galindo, Max Hardy, Raúl Del Rey-Vergara, Albert Iñañez, Beatriz Sanchez-Espiridion, Laura Moliner, Sergi Clavé, Beatriz Bellosillo, Ana Rovira, Júlia Perera-Bel, Ignacio Wistuba, Edurne Arriola, Luisa M. Solis, Pedro Rocha. Spatial proteomic profiling unveils pre-existing anti-tumor immunity as a hallmark of exceptional benefit from immunotherapy in NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6391.

Abstract 7380: Predicting immunotherapy outcomes from H&E images in lung cancer

Abstract Checkpoint blockade immunotherapy is a cornerstone of lung cancer treatment, but there is a need to improve the identification of patients who will respond favorably. Here, we explored a deep learning approach to predict immunotherapy outcomes from hematoxylin and eosin (H&E) images in non-small cell lung cancer (NSCLC). We included 150 unique cases with metastatic NSCLC (113 adenocarcinoma, 29 squamous cell, 8 other) treated with anti-PD-1/PD-L1 immunotherapy (56 nivolumab, 49 atezolizumab, 44 pembrolizumab, 1 durvalumab) as mono or combination (14 with chemotherapy, 1 with ipilimumab) therapy in a single institution. Each case consisted of a representative H&E whole slide image (53 biopsies, 50 needle core biopsies, 47 resections) obtained prior to immunotherapy, and the outcome reported as the 1-year overall survival (OS). PD-L1 status (tumor proportion score ≥ 1%) was known for 70 cases. We preprocessed the H&E images using two deep learning models previously developed using The Cancer Genome Atlas dataset. First, we used a classification model to identify tumor regions and randomly sampled a fixed number of tumor patches for each case. Then, we used a self-supervised pathology foundation model to obtain a compressed visual representation of each patch, known as an embedding. Next, using our dataset, we trained a deep multiple instance learning (DeepMIL) model with a gated attention mechanism to predict the binary 1-year OS status (0=deceased, 1=alive) for each case. As a baseline, we also trained a linear-probe (logistic regression) model using the averaged embeddings. Given the small dataset size, 5-fold cross-validation was used to train and evaluate both the DeepMIL and linear-probe models, with cases randomly split across folds. For evaluation, we used survival analysis to compare the 0/1 case groups. Overall, across all 150 cases, univariable Cox regression showed that 1-year OS was more strongly associated with the DeepMIL status (46/104, HR=0.55, p=0.03) than the linear-probe status (55/95, HR=0.81, p=0.44). Results were consistent on the subset of 70 cases with known PD-L1 status, whereby OS was most strongly associated with the DeepMIL status (19/51, HR=0.40, p=0.04) compared to the linear-probe status (31/39, HR=0.46, p=0.09) and PD-L1 status (30/40, HR=0.65, p=0.32). In multivariable Cox regression adjusting for age group and smoking status, OS remained more strongly associated with the DeepMIL status (HR=0.45, p=0.08) than PD-L1 status (HR=0.72, p=0.47). In conclusion, the DeepMIL status predicted from H&E images showed a stronger association with outcomes compared to PD-L1 status, a standard biomarker for immunotherapy in NSCLC. These exploratory results demonstrate the potential of deep learning using pathology foundation models to improve immunotherapy outcomes prediction, even with small datasets. Such approaches may even enable the discovery of novel biomarkers from H&E images to advance precision medicine. Citation Format: Jessica Loo, Yang Wang, Pok Fai Wong, Ellery Wulczyn, Jeremy Lai, Peter Cimermancic, David F. Steiner, Shamira S. Weaver. Predicting immunotherapy outcomes from H&E images in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7380.

Abstract 7323: Tissue resident memory T cell abundances impact non-small-cell lung cancer immune microenvironment and patient prognosis

Abstract Tissue resident memory T cells (TRM) are a specialized subset of long-lived memory T cells that reside in peripheral tissues. However, whether TRM exerts any immunosurveillance role in the tumor immune microenvironment (TIME) and progression of non-small-cell lung cancer (NSCLC), which accounts for 85% of all lung cancers, remains unclear. Our comprehensive analysis of multiple independent single-cell and bulk RNA-seq datasets of patient NSCLC samples generated reliable, unique TRM signatures, through which we could infer the abundance of TRM in NSCLC. We discovered that TRM abundance is consistently positively correlated with CD4+ T helper 1 cells, M1 macrophages, and resting dendritic cells in TIME and significantly impacts the prognosis of NSCLC patients. In addition, TRM signatures are strongly associated with immune checkpoint genes and the prognosis of NSCLC patients, suggesting that TRM signatures are promising prognostic markers for immunotherapy in NSCLC. We then built a machine learning model to predict patient survival based on the TRM signatures and immune related genes. The accuracy of the model was validated by Kaplan-Meyer survival analysis, receiver operating characteristic curves, principal component analysis, and t-distributed random neighbor embedding. We developed a 4-gene risk score that effectively stratified patients into low-risk and high-risk categories. The patients with high-risk scores had significantly lower overall survival than patients with low-risk. The prognostic value of the risk score was independently validated by the Cancer Genome Atlas Program (TCGA) dataset and multiple independent NSCLC patient datasets. Notably, low-risk NSCLC patients with higher TRM infiltration exhibited enhanced T-cell activation, macrophage regulation, and other TIME immune responses related pathways, indicating a more active immune profile benefitting from immunotherapy. Altogether, this study provides valuable insights into the complex interactions between NSCLC TRM and TIME and their impact on patient prognosis, highlighting the importance of TRM in shaping the NSCLC microenvironment. The development of a simplified 4-gene risk score provides a practical prognostic marker for risk stratification. Keywords: Tissue resident memory T cell, non-small-cell lung cancer, prognosis, tumor immune microenvironment, machine learning Citation Format: Aidan Shen, Aliesha Garrett, Junhua Mai, Yangzhi Zhu, Chongming Jiang. Tissue resident memory T cell abundances impact non-small-cell lung cancer immune microenvironment and patient prognosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7323.

Abstract 5101: Comparative genomic analysis reveals distinctive immune profiles in MET exon 14 mutated and MET amplified lung cancer

Abstract Background: In non-small cell lung cancer (NSCLC), the MET tyrosine kinase receptor can be mutated or amplified resulting in dysregulation of receptor function leading to tumor proliferation. MET exon 14 (METEx14) mutated and MET amplified NSCLC tumors have shown varied response to immunotherapy. Therefore, we sought to compare the genomic and immune landscape of MET-altered NSCLC. Methods: The genomic profiles of 3,821 NSCLC tumors sequenced using the Strata Select assay on the Strata Oncology Platform were analyzed. Tumors were sorted based on METex14 mutations, MET amplification (METamp) defined as copy number gain (CNG) ≥6 and MET wild-type (METwt). The RNA expression of 19 immune regulatory genes, tumor mutation burden (TMB), Strata Immunotherapy Response Signature (IRS) score and the frequency of gene co-alterations were compared across groups. Statistical comparisons of medians were done with Kruskal-Wallis testing and categorical comparisons with Chi square using R Studio version 4.3.2. Results: 122 (3.2%) METex14, 70 (1.8%) METamp, and 3,629 (95.0%) METwt were identified. Patients with METex14 were older and more frequently female. MET gene expression was found to be higher in METamp (median 14.4) compared to METex14 (median 12.3) (P<0.01). TMB was lowest in METex14 (median 2.7) group compared to METamp (median 7.1) and METwt (median 5.1) (P<0.001). High PD-L1 expression occurred in 71.4% of METamp, 68.0% of METex14 and 41.3% of METwt (P<0.001). Overall, METamp tumors had a greater proportion of high IRS scores (52.9%) compared to METex14 (35.2%) and METwt (45.4%) (P<0.01). mRNA expression of immune checkpoints CTLA4, PD-1, LAG3, IDO1, TIGIT and HAVCR2 were all higher in METex14 compared to METamp and METwt (P<0.001 for all). METex14 tumors also exhibited higher gene expression of CD4, CD8A and FOXP3 compared to METamp and METwt (p<0.001). METex14 had higher prevalence of MDM2 amplification (34% vs 3% vs 4%) and lower prevalence of alterations in EGFR (0.8% vs 22% vs 21%), KRAS (0.8% vs 10% vs 26%), CDKN2A (17% vs 29% v 28%) and TP53 (34% vs 87% vs 64%) compared with METamp and METwt tumors, respectively (p<0.05). Conclusion: METex14 and METamp tumors harbor distinct immune-gene expression profiles and co-occurring gene alterations that distinguish themselves from each other and METwt tumors. Further analysis must be conducted to determine how these variations impact immunotherapy in MET-altered NSCLC. Citation Format: Saahil Javeri, Rachel Minne, Shrey Ramesh, Andrew Baschnagel, Randy Kimple, Laura Lamb, Scott Tomlins, Bryan Johnson, Nickolay Khazanov. Comparative genomic analysis reveals distinctive immune profiles in MET exon 14 mutated and MET amplified lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5101.

Identification of cellular senescence-associated genes as new biomarkers for predicting the prognosis and immunotherapy response of non-small cell lung cancer and construction of a prognostic model

BackgroundGlobally, lung carcinoma remains the leading cause of death, with its associated morbidity and mortality rates remaining elevated. Despite the slow advancement of treatment, the outlook remains bleak. Cellular senescence represents a halt in the cell cycle, encompassing a range of physiological and pathological activities, along with diverse phenotypic alterations, including variations in secretory phenotype, macromolecular harm, and metabolic disturbances. Research has revealed its vital function in the formation and growth of tumors. This study aimed to examine cellular senescence-related mRNAs linked to the outlook of non-small cell lung cancer (NSCLC) and to formulate a predictive risk framework for NSCLC. MethodsWe acquired the NSCLC expression data from The Cancer Genome Atlas (TCGA) to examine mRNAs linked to cellular senescence. Both single-variable and multiple-variable cox proportion risk assessments were utilized to determine the traits of cellular senescence-related mRNAs linked to NSCLC prognosis. Subsequently, the prognostic model for cellular senescence-related mRNAs was integrated with clinical-pathological characteristics to create a prognostic nomogram. Furthermore, the study delved into the risk-oriented predictive model, examining immune infiltration and responses to immunotherapy among both high and low-risk categories. ResultsUtilizing both univariate and multivariate Cox proportion risk assessments, a risk model comprising 12 mRNAs associated with cellular aging was ultimately developed: IGFBP1, TLR3, WT1, ID1, PTTG1, ERRFI1, HEPACAM, MAP2K3, RAD21, NANOG, PRKCD, SOX5. Univariate analysis and multivariate analysis illustrated that the risk score served as a standalone indicator for prognosis, and the hazard ratio (HR) of the risk score were 1.182 (1.139–1.226) (p < 0.001) and 1.162 (1.119 − 1.206) (p < 0.001), respectively. Individual prognoses were forecasted using nomogram, c-index, and principal component analysis (PCA). Furthermore, the risk-oriented model revealed notable statistical variances in immune infiltration and response to immunotherapy among the high and low risk categories. ConclusionsThis study shows that mRNAs related to cell senescence associated with prognosis are reliable predictors of NSCLC immunotherapy reaction and prognosis.

Dual immunotherapy in advanced or metastatic non-small cell lung cancer: A network meta-analysis

Recently, there has been extensive research on dual immunotherapy for advanced or metastatic non-small cell lung cancer (NSCLC), yet a comprehensive evaluation is lacking. This study aimed to rank the available treatment options and assess the efficacy and safety of dual immunotherapy regimens through the implementation of a Bayesian network meta-analysis (NMA). A thorough search was conducted to recognize eligible randomized controlled trials (RCTs) on March 20, 2023. Overall survival (OS), progression-free survival (PFS), treatment-related adverse events (TRAEs) and grade ≥3 TRAEs were evaluated to identify the efficacy and safety of dual immunotherapy regimens. The surface under the cumulative ranking curve (SUCRA) and P score were employed to rank the treatments. Eleven clinical trials involving six different regimens were included in this study. The combination of anti-programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) antibodies with anti-T-cell immunoglobulin and ITIM domain (TIGIT) antibodies emerged as the most promising regimen for improving OS and PFS, followed by anti-PD-1/PD-L1+anti-cytotoxic T lymphocyte antigen 4 (CTLA-4)+chemotherapy treatment and anti-PD-1/PD-L1+anti-CTLA-4 treatment. The forest plots demonstrated that these three regimens were all superior to chemotherapy. The above results were observed in both unselected treatment line and first-line settings. The least likely to be associated with TRAEs and grade ≥3 TRAEs were respectively anti-CTLA-4 treatment and anti-PD-1/PD-L1+anti-TIGIT treatment, with anti-PD-1/PD-L1+anti-CTLA-4+chemotherapy treatment to be the worst. This NMA validated the promising efficacy and safety of dual immunotherapy in advanced or metastatic NSCLC. Among them, anti-PD-1/PD-L1+anti-TIGIT regimen emerges as a highly potential therapeutic approach. Ongoing research efforts should focus on improving treatment regimens, identifying biomarkers, and managing TRAEs to optimize the patient benefits of dual immunotherapy.

MAIT cells are associated with responsiveness to neoadjuvant immunotherapy in COPD-associated NSCLC.

Patients with non-small cell lung cancer (NSCLC) and chronic obstructive pulmonary disease (COPD) experience worse clinical outcomes but respond better to immunotherapy than patients with NSCLC without COPD. Mucosal-associated invariant T (MAIT) cells, a versatile population of innate immune T lymphocytes, have a crucial function in the response to infection and tumors. This study investigated the distribution of MAIT cells in COPD-associated NSCLC and their involvement in the immune response. Flow cytometry, immunohistochemistry, and immunofluorescence were performed on tissue samples of patients with NSCLC, with or without COPD, treated with or without anti-programmed death 1 (PD1) immunotherapy. MAIT cells were stimulated with 5-OP-RU using a mouse subcutaneous tumor model. Tumors contained significantly more MAIT cells than paraneoplastic tissues, and CD8+ MAIT cells accounted for more than 90% of these cells. Patients with NSCLC and COPD had higher CD8+ MAIT cell counts than those with NSCLC without COPD. Additionally, patients with NSCLC and COPD displayed reduced expression of the activation marker, CD69, and functional markers, granzyme B (GZMB) and interferon γ (IFNγ), and higher expression of the immune exhaustion marker, PD1. Among patients who received immunotherapy, the proportion with a complete or partial response was higher in those with COPD than in those without COPD. In patients with NSCLC and COPD, the major pathologic response (MPR) group had higher MAIT levels than those in the no major pathologic response (NPR) group. In the mouse subcutaneous tumor model stimulation of MAIT cells using 5-OP-RU enhanced the antitumor effects of anti-PD1. In patients with NSCLC and COPD, response to immunotherapy is associated with accumulation of CD8+ MAIT cells showing immune exhaustion. These findings may contribute to innovative approaches for immunotherapy targeting CD8+ MAIT cells.

Identification of macrophage-related genes correlated with prognosis and immunotherapy efficacy in non-small cell lung cancer

BackgroundMalignant tumours, particularly non-small cell lung cancer (NSCLC), pose a significant threat to human health due to their prevalence and lethality. Treatment methods for NSCLC vary greatly among individuals, making it crucial to identify predictive markers. Moreover, during tumour initiation and progression, tumour cells can release signaling molecules to induce polarization of macrophages towards a more tumour friendly M2 phenotype, which can promote tumour growth, metastasis, and drug resistance. MethodsWe employed a comprehensive approach, combining bulk RNA-seq and single-cell sequencing analysis. ResultsIn our study, we used bulk RNA-seq and single-cell sequencing methods to analyze differential cells in NSCLC and adjacent tissues, searching for relevant marker genes that can predict prognosis and drug efficacy. We scrutinized biological phenomena such as macrophage-related gene methylation, copy number variation, and alternative splicing. Additionally, we utilized a co-culture technique of immune and tumour cells to explore the role of these genes in macrophage polarization. Our findings revealed distinct differences in macrophages between cancerous and adjacent tissues. We identified ANP32A, CCL20, ERAP2, MYD88, TMEM126B, TUBB6, and ZNF655 as macrophage-related genes that correlate with NSCLC patient prognosis and immunotherapy efficacy. Notably, ERAP2, TUBB6, CCL20, and TMEM126B can induce macrophage M0 to M2 polarization, promoting tumour proliferation. ConclusionThese findings significantly contribute to our understanding of the NSCLC tumour immune microenvironment. They pave the way for further research into the potential of these genes as targets for regulating tumour occurrence and development.

Perioperative immunotherapy: the main clinical treatment for resectable non-small cell lung cancer.

Phase 3 clinical trials of perioperative immunotherapy for resectable non-small cell lung cancer (NSCLC): In recent years, immunotherapy for NSCLC is not only limited to advanced disease, but also has shown gratifying efficacy for early resectable NSCLC. With the publication of the results of several phase 3 clinical trials, perioperative immunotherapy will become one of the main treatment modalities for resectable NSCLC.

Dynamic surveillance of lymphocyte subsets in patients with non-small cell lung cancer during chemotherapy or combination immunotherapy for early prediction of efficacy.

Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related deaths worldwide. Lymphocytes are the primary executors of the immune system and play essential roles in tumorigenesis and development. We investigated the dynamic changes in peripheral blood lymphocyte subsets to predict the efficacy of chemotherapy or combination immunotherapy in NSCLC. This retrospective study collected data from 81 patients with NSCLC who received treatments at the First Affiliated Hospital of Zhengzhou University from May 2021 to May 2023. Patients were divided into response and non-response groups, chemotherapy and combination immunotherapy groups, and first-line and multiline groups. We analyzed the absolute counts of each lymphocyte subset in the peripheral blood at baseline and after each treatment cycle. Within-group and between-group differences were analyzed using paired Wilcoxon signed-rank and Mann-Whitney U tests, respectively. The ability of lymphocyte subsets to predict treatment efficacy was analyzed using receiver operating characteristic curve and logistic regression. The absolute counts of lymphocyte subsets in the response group significantly increased after the first cycle of chemotherapy or combination immunotherapy, whereas those in the non-response group showed persistent decreases. Ratios of lymphocyte subsets after the first treatment cycle to those at baseline were able to predict treatment efficacy early. Combination immunotherapy could increase lymphocyte counts compared to chemotherapy alone. In addition, patients with NSCLC receiving chemotherapy or combination immunotherapy for the first time mainly presented with elevated lymphocyte levels, whereas multiline patients showed continuous reductions. Dynamic surveillance of lymphocyte subsets could reflect a more actual immune status and predict efficacy early. Combination immunotherapy protected lymphocyte levels from rapid decrease and patients undergoing multiline treatments were more prone to lymphopenia than those receiving first-line treatment. This study provides a reference for the early prediction of the efficacy of clinical tumor treatment for timely combination of immunotherapy or the improvement of immune status.

KEAP1 promotes anti-tumor immunity by inhibiting PD-L1 expression in NSCLC

Immunotherapy has become a prominent first-line cancer treatment strategy. In non-small cell lung cancer (NSCLC), the expression of PD-L1 induces an immuno-suppressive effect to protect cancer cells from immune elimination, which designates PD-L1 as an important target for immunotherapy. However, little is known about the regulation mechanism and the function of PD-L1 in lung cancer. In this study, we have discovered that KEAP1 serves as an E3 ligase to promote PD-L1 ubiquitination and degradation. We found that overexpression of KEAP1 suppressed tumor growth and promoted cytotoxic T-cell activation in vivo. These results indicate the important role of KEAP1 in anti-cancer immunity. Moreover, the combination of elevated KEAP1 expression with anti-PD-L1 immunotherapy resulted in a synergistic effect on both tumor growth and cytotoxic T-cell activation. Additionally, we found that the expressions of KEAP1 and PD-L1 were associated with NSCLC prognosis. In summary, our findings shed light on the mechanism of PD-L1 degradation and how NSCLC immune escape through KEAP1-PD-L1 signaling. Our results also suggest that KEAP1 agonist might be a potential clinical drug to boost anti-tumor immunity and improve immunotherapies in NSCLC.

Subsequent surgical treatment or maintenance immunotherapy in stage III lung cancer patients achieving a favorable response following neoadjuvant immunotherapy: A matched retrospective cohort study from the surgical perspective.

Current treatment strategies for advanced non-small cell lung cancer (NSCLC) are highly individualized and subject to ongoing debates. In the era of immunotherapy, surgery assumes a critical role. The aim of this study was to investigate if subsequent surgical intervention, following a favorable response to immunotherapy and chemotherapy, could yield a more favorable prognosis for patients with advanced stage III NSCLC compared to the continuation of immunotherapy and chemotherapy. We included patients whose tumors exhibited a favorable response (including partial response [PR] and complete response [CR]) to immunotherapy and chemotherapy. These patients were categorized into two groups based on their subsequent treatment plans: surgical and nonsurgical (continuation of maintenance immunotherapy and chemotherapy). The efficacy and long-term prognosis of these groups were compared after matching them in a 1:1 ratio using propensity scores. In total, 186 patients (93 in each group) were included in this study after matching via propensity scores. The 1- and 3-year overall survival (OS) and progression-free survival (PFS) rates were 96.0%, 88.5%, and 93.1%, 80.7% in the surgical group, and 93.2%, 83.1%, and 57.7%, 50.4% in the nonsurgical group, respectively. Patients in the surgical group exhibited significantly superior PFS and OS compared to those in the nonsurgical group (p = 0.025 and p = 0.00086). Univariate and multivariate analyses confirmed ΔBMI, Δtumor size reduction, tumor response, earlier clinical stage (IIIb vs. IIIa), and surgery as independent protective factor for patient prognosis. We further selected 101 patients with CR (39 in the surgical group and 62 in the nonsurgical group) and found that patients in the surgical group were significantly better in both PFS and OS. Our subgroup analysis in postoperative patients demonstrated that different surgical strategies did not significantly affect the long-term prognosis of patients (PFS and OS) but could impact their perioperative experience. Patients with advanced stage III NSCLC, whose tumors achieved PR and CR after 2-4 cycles of immunotherapy combined with chemotherapy, experience a more promising prognosis with subsequent surgical intervention compared with the continued immunotherapy. Despite encountering formidable obstacles, such as protracted surgical procedures and associated trauma, we must rise to the challenge and unleash the power of surgery after immunotherapy in advanced NSCLC.

MicroRNA-126 selected with broad-spectrum analysis of microRNAs - a new predictive factor for the effectiveness of immunotherapy or chemoimmunotherapy in advanced NSCLC patients?

Expression of PD-L1 on cancer cells is the only validated predictive factor for immunotherapy in NSCLC (Non-Small Cell Lung Cancer) patients. However, on this basis, it is difficult to predict the occurrence of resistance to immune checkpoint inhibitors (ICIs). MicroRNAs are widely studied as biomarkers of cancers. Our study was designed to determine whether microRNAs can be sensitive predictive factors in the qualification of NSCLC patients to first-line immunotherapy or chemoimmunotherapy. The two-stage research on validation group (n=20) and study group (n=35) of patients with advanced NSCLC was conducted. Analysis of microRNAs expression by qPCR in plasma collected prior to the start of immunotherapy (pembrolizumab) or chemoimmunotherapy (combination ofpembrolizumab with chemotherapy) was made. Broad-spectrum analysis of microRNAs expression was used in the studied group. Three microRNAs selected in that group as important for the effectiveness of ICIs were then examined in the validation group. In the studied group, significantly higher expression of miRNA-126-3p, miR-144-3p and miR-146-5p was observed in patients with long PFS compared to those with short PFS. In the validation group, low miRNA-126 expression indicated lower median progression-free survival and overall survival (2.3 vs. 5.0 months and 5.2 vs 11.2, respectively). These patients had a significantly higher risk of progression (HR= 2.92, 95% CI: 1.01 to 8.40, p=0.04) and death (HR=3.64, 95% CI: 1.22 to 10.84, p=0.02). Our study showed that the expression of miR-126 in blood plasma may be a predictive factor for the effectiveness of first-line immunotherapy or chemoimmunotherapy in advanced NSCLC patients.

Predicting programmed death-ligand 1 (PD-L1) expression with fluorine-18 fluorodeoxyglucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) metabolic parameters in resectable non-small cell lung cancer.

Programmed death-ligand 1 (PD-L1) expression is a predictive biomarker for immunotherapy in non-small cell lung cancer (NSCLC). PD-L1 and glucose transporter 1 expression are closely associated, and studies demonstrate correlation of PD-L1 with glucose metabolism. The aim of this study was to investigate the association of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG-PET/CT) metabolic parameters with PD-L1 expression in primary lung tumour and lymph node metastases in resected NSCLC. We conducted a retrospective analysis of 210 patients with node-positive resectable stage IIB-IIIB NSCLC. PD-L1 tumour proportion score (TPS) was determined using the DAKO 22C3 immunohistochemical assay. Semi-automated techniques were used to analyse pre-operative [18F]FDG-PET/CT images to determine primary and nodal metabolic parameter scores (including max, mean, peak and peak adjusted for lean body mass standardised uptake values (SUV), metabolic tumour volume (MTV), total lesional glycolysis (TLG) and SUV heterogeneity index (HISUV)). Patients were predominantly male (57%), median age 70 years with non-squamous NSCLC (68%). A majority had negative primary tumour PD-L1 (TPS < 1%; 53%). Mean SUVmax, SUVmean, SUVpeak and SULpeak values were significantly higher (p < 0.05) in those with TPS ≥ 1% in primary tumour (n = 210) or lymph nodes (n = 91). However, ROC analysis demonstrated only moderate separability at the 1% PD-L1 TPS threshold (AUCs 0.58-0.73). There was no association of MTV, TLG and HISUV with PD-L1 TPS. This study demonstrated the association of SUV-based [18F]FDG-PET/CT metabolic parameters with PD-L1 expression in primary tumour or lymph node metastasis in resectable NSCLC, but with poor sensitivity and specificity for predicting PD-L1 positivity ≥ 1%. Whilst SUV-based fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography metabolic parameters may not predict programmed death-ligand 1 positivity ≥ 1% in the primary tumour and lymph nodes of resectable non-small cell lung cancer independently, there is a clear association which warrants further investigation in prospective studies. Non-applicable KEY POINTS: • Programmed death-ligand 1 immunohistochemistry has a predictive role in non-small cell lung cancer immunotherapy; however, it is both heterogenous and dynamic. • SUV-based fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG-PET/CT) metabolic parameters were significantly higher in primary tumour or lymph node metastases with positive programmed death-ligand 1 expression. • These SUV-based parameters could potentially play an additive role along with other multi-modal biomarkers in selecting patients within a predictive nomogram.